The primary goal of dynamic building envelopes is to meet and balance antagonistic performance criteria utilizing automatic operation. As opposed to static systems, automated shading and daylighting ...systems are increasingly being used in façade design with the intent to improve building performance. Taking this into consideration, the question that arises is whether such systems can significantly improve buildings energy performance and occupants׳ visual and thermal comfort. The present paper is a review of dynamic operation methods of shading/daylighting systems and their associated implications in building energy balance. Based on the subject distribution of the reviewed studies, the majority of the systems examined are versions of motorized blinds while the analysis of new emerging ideas on deployable and foldable façade systems is limited. User acceptance is quite crucial and is strongly dependent on the system׳s intuitive operation. According to the paper findings, energy savings with automatically controlled blinds depend on the type of control strategy and their connection to dimmable electric lighting systems. Even though control strategies enhance energy performance and occupants׳ comfort, their level of complexity highly affects their efficiency and therefore influences their performance.
Moving Forward Fried, Eiko I.; Cramer, Angélique O. J.
Perspectives on psychological science,
11/2017, Letnik:
12, Številka:
6
Journal Article
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Since the introduction of mental disorders as networks of causally interacting symptoms, this novel framework has received considerable attention. The past years have resulted in over 40 scientific ...publications and numerous conference symposia and workshops. Now is an excellent moment to take stock of the network approach: What are its most fundamental challenges, and what are potential ways forward in addressing them? After a brief conceptual introduction, we first discuss challenges to network theory: (1) What is the validity of the network approach beyond some commonly investigated disorders such as major depression? (2) How do we best define psychopathological networks and their constituent elements? And (3) how can we gain a better understanding of the causal nature and real-life underpinnings of associations among symptoms? Next, after a short technical introduction to network modeling, we discuss challenges to network methodology: (4) heterogeneity of samples studied with network analytic models, and (5) a lurking replicability crisis in this strongly data-driven and exploratory field. Addressing these challenges may propel the network approach from its adolescence into adulthood and promises advances in understanding psychopathology both at the nomothetic and idiographic level.
This paper is intended to present a new harmonic selection technique when solving nonlinear dynamic systems with the harmonic balance method. This technique belongs to the class of method called the ...adaptive harmonic balance method (AHBM). The harmonic selection is based on the use of a tangent predictor and relies on a stepwise regression procedure that allows for a dynamic management of the number of selected harmonics via an addition or removal procedure. The efficiency of this method relative to the classical harmonic balance method (HBM) is then evaluated through examples; this later step will indicate that AHBM can significantly reduce the number of variables, thus leading to computational time savings without deteriorating solution quality.
► Selection relies upon tangent predictor and a spectral energy. ► The algorithm is not incremental. ► The number of retained Fourier coefficients varies with both dof and frequency. ► Procedure allows for time savings without deteriorating the quality of solutions.
Weather regimes have been defined over multiple regions and used in a range of practical applications, including subseasonal‐to‐seasonal forecasting and climate model evaluation. Despite their ...widespread use, the extent to which regimes reflect physical modes of the atmosphere is seldom investigated. Here, we adopt a year‐round classification of four North American weather regimes, with a fifth “no regime” class, and leverage dynamical systems theory to investigate their dynamical properties. We find that when the atmospheric flow is assigned to a regime, it displays persistent characteristics and a lifecycle‐like temporal evolution. We further find that, regardless of season, these characteristics are enhanced when the atmospheric flow displays a comparatively strong projection onto the cluster‐mean of the regime to which it is assigned (while the reverse is true for a weaker projection). We interpret these results as evidence that the four North American weather regimes are physically‐meaningful, with a clear dynamical footprint.
Plain Language Summary
Surface weather and extremes in North America can be related to a small number of atmospheric patterns stretching over scales of thousands of kilometers. These patterns, known as weather regimes, vary over timescales of several days to weeks and occur repeatedly: depending on the exact definition, between a third and a fifth of all days typically fall within a given regime. Weather regimes have a number of practical applications, hinging around making statistical predictions of the weather over a large region several weeks in advance. Even though they have proven useful in practice, there is no simple way of determining to what extent weather regimes are actually linked to the dynamics and physics of the atmosphere. While different definitions of weather regimes exist for different seasons, there have been recent efforts to identify weather regimes that may be applicable year‐round. In this study, we adopt a four‐regime, year‐round classification for the North American continent, and investigate whether the regimes have a clear physical footprint. We find that when the atmosphere falls within a given regime, it displays persistent flow characteristics with a systematic evolution in time. These results support interpreting the regimes as physically‐meaningful, rather than simply a statistical characterization of atmospheric patterns.
Key Points
Four year‐round North American regimes exhibit a clear dynamical footprint, supporting their interpretation as physically‐meaningful
The regimes are persistent atmospheric states with a coherent lifecycle‐like temporal evolution
The stronger the atmospheric flow projects onto the assigned regime, the more evident the above properties become
This paper is concerned with the observer design problem for a class of multi-input-multi-output nonlinear systems with the unmodeled dynamics, unknown parameters and external disturbance. A dynamic ...signal, which can dominate the unmodeled dynamics, is firstly constructed. Then, two types of observer schemes, that is, adaptive observer and robust observer, are respectively proposed. The observation error in the two schemes can be made arbitrarily small by choosing the appropriate design parameters. An illustrative example is provided to demonstrate the validity of the proposed design methods.
This paper presents a fault detection and isolation (FDI) scheme for a class of Lipschitz nonlinear systems with nonlinear and unstructured modeling uncertainty. This significantly extends previous ...results by considering a more general class of system nonlinearities which are modeled as functions of the system input and partially measurable state variables. A new FDI method is developed using adaptive estimation techniques. The FDI architecture consists of a fault detection estimator and a bank of fault isolation estimators. The fault detectability and isolability conditions, characterizing the class of faults that are detectable and isolable by the proposed scheme, are rigorously established. The fault isolability condition is derived via the so-called fault mismatch functions, which are defined to characterize the mutual difference between pairs of possible faults. A simulation example of a single-link flexible joint robot is used to illustrate the effectiveness of the proposed scheme.